Search ga_ls9c_ard_3 whole collection

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels. For these ARD products, this value comes from the Fmask algorithm. from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels. For these ARD products, this value comes from the Fmask algorithm. to (exclusive):

Time when dataset was created (processed) From

Time when dataset was created (processed) to (exclusive)

The raw CRS string as it appears in metadata:

One of - final|interim|nrt (near real time):

ID of a dataset type:

Ground sampling distance of the sensor’s best resolution band in metres; represents the size (or spatial resolution) of one pixel. from:

Ground sampling distance of the sensor’s best resolution band in metres; represents the size (or spatial resolution) of one pixel. to (exclusive):

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north from:

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north to (exclusive):

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon. from:

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon. to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to the Fmask algorithm from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to the Fmask algorithm to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud shadow pixels according to the Fmask algorithm from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud shadow pixels according to the Fmask algorithm to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains clear snow pixels according to the Fmask algorithm from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear snow pixels according to the Fmask algorithm to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains clear water pixels according to the Fmask algorithm from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear water pixels according to the Fmask algorithm to (exclusive):

File format (GeoTiff, NetCDF):

GQA Circular error probable (90%) from:

GQA Circular error probable (90%) to (exclusive):

Mean of the absolute values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the absolute values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the absolute values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the absolute values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the absolute values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the absolute values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Absolute value of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Absolute value of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Absolute value of the total GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Absolute value of the total GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Absolute value of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Absolute value of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Circular error probable (90%) of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Circular error probable (90%) of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Dataset UUID:

User who indexed the dataset:

When dataset was indexed:

Label:

A Landsat Collection 1 Level-1 product identifier including the Collection processing levels, processing date, collection number, and collection tier category (e.g. ‘LE07_L1TP_098084_20210307_20210308_02_RT’) :

A Landsat scene ID including WRS path and row, year and day, ground station identifier and archive version number (e.g. ‘LC80900852021066LGN00’) :

Latitude range from:

Latitude range to (exclusive):

Longitude range from:

Longitude range to (exclusive):

Full metadata document:

Metadata type name of dataset:

ID of a metadata type:

Spatial reference code from the provider. For Landsat region_code is a scene path row: '{:03d}{:03d}.format(path,row)' For Sentinel it is MGRS code. In general it is a unique string identifier that datasets covering roughly the same spatial region share. :

Acquisition time range From

Acquisition time range to (exclusive)

Dataset URI:

Add field

54 results

Time (local)	Label
2021-11-07 09:22:39	ga_ls9c_ard_3-2-1_090088_2021-11-06_final.stac-item
2021-11-13 10:01:54	ga_ls9c_ard_3-2-1_097080_2021-11-13_final.stac-item
2022-02-11 09:40:03	ga_ls9c_ard_3-2-1_094071_2022-02-11_final.stac-item
2022-05-18 11:20:39	ga_ls9c_ard_3-2-1_110077_2022-05-18_final.stac-item
2022-05-27 11:13:38	ga_ls9c_ard_3-2-1_109075_2022-05-27_final.stac-item
2022-05-31 09:10:50	ga_ls9c_ard_3-2-1_089077_2022-05-30_final.stac-item
2022-06-12 11:17:18	ga_ls9c_ard_3-2-1_109084_2022-06-12_final.stac-item
2022-06-16 09:10:57	ga_ls9c_ard_3-2-1_089077_2022-06-15_final.stac-item
2022-06-28 11:14:24	ga_ls9c_ard_3-2-1_109076_2022-06-28_final.stac-item
2022-07-12 11:23:30	ga_ls9c_ard_3-2-1_111068_2022-07-12_final.stac-item
2022-07-15 11:57:35	ga_ls9c_ard_3-2-1_116076_2022-07-15_final.stac-item
2022-08-01 09:22:57	ga_ls9c_ard_3-2-1_091075_2022-07-31_final.stac-item
2022-08-01 09:28:08	ga_ls9c_ard_3-2-1_091088_2022-07-31_final.stac-item
2022-08-23 10:28:06	ga_ls9c_ard_3-2-1_101083_2022-08-23_final.stac-item
2022-09-01 11:58:25	ga_ls9c_ard_3-2-1_116077_2022-09-01_final.stac-item
2022-10-06 09:11:40	ga_ls9c_ard_3-2-1_089077_2022-10-05_final.stac-item
2022-10-18 09:39:17	ga_ls9c_ard_3-2-1_093084_2022-10-18_final.stac-item
2022-12-23 09:24:52	ga_ls9c_ard_3-2-1_091079_2022-12-22_final.stac-item
2023-01-02 10:00:01	ga_ls9c_ard_3-2-1_097074_2023-01-02_final.stac-item
2023-01-22 11:14:02	ga_ls9c_ard_3-2-1_109074_2023-01-22_final.stac-item
2023-01-24 11:02:31	ga_ls9c_ard_3-2-1_107076_2023-01-24_final.stac-item
2023-03-12 10:19:27	ga_ls9c_ard_3-2-1_100077_2023-03-12_final.stac-item
2023-03-22 09:17:36	ga_ls9c_ard_3-2-1_090077_2023-03-21_final.stac-item
2023-04-12 11:14:00	ga_ls9c_ard_3-2-1_109075_2023-04-12_final.stac-item
2023-04-15 10:02:24	ga_ls9c_ard_3-2-1_098066_2023-04-15_final.stac-item
2023-05-14 11:13:45	ga_ls9c_ard_3-2-1_109075_2023-05-14_final.stac-item
2023-06-07 10:26:54	ga_ls9c_ard_3-2-1_101082_2023-06-07_final.stac-item
2023-07-04 11:45:44	ga_ls9c_ard_3-2-1_114078_2023-07-04_final.stac-item
2023-07-05 09:12:26	ga_ls9c_ard_3-2-1_089081_2023-07-04_final.stac-item
2023-07-12 09:21:05	ga_ls9c_ard_3-2-1_090087_2023-07-11_final.stac-item
2023-07-15 11:23:18	ga_ls9c_ard_3-2-1_111068_2023-07-15_final.stac-item
2023-08-03 10:19:01	ga_ls9c_ard_3-2-1_100077_2023-08-03_final.stac-item
2023-09-03 11:14:29	ga_ls9c_ard_3-2-1_109076_2023-09-03_final.stac-item
2023-10-03 09:46:53	ga_ls9c_ard_3-2-1_095073_2023-10-03_final.stac-item
2023-10-03 11:23:47	ga_ls9c_ard_3-2-1_111068_2023-10-03_final.stac-item
2023-10-10 09:58:20	ga_ls9c_ard_3-2-1_096086_2023-10-10_final.stac-item
2023-10-28 09:45:37	ga_ls9c_ard_3-2-1_094085_2023-10-28_final.stac-item
2023-11-07 10:19:28	ga_ls9c_ard_3-2-1_100077_2023-11-07_final.stac-item
2023-11-10 10:46:23	ga_ls9c_ard_3-2-1_105067_2023-11-10_final.stac-item
2023-11-11 11:31:39	ga_ls9c_ard_3-2-1_112072_2023-11-11_final.stac-item
2023-12-06 11:24:44	ga_ls9c_ard_3-2-1_111070_2023-12-06_final.stac-item
2023-12-09 10:19:32	ga_ls9c_ard_3-2-1_100077_2023-12-09_final.stac-item
2023-12-12 09:11:36	ga_ls9c_ard_3-2-1_089077_2023-12-11_final.stac-item
2023-12-12 09:12:23	ga_ls9c_ard_3-2-1_089079_2023-12-11_final.stac-item
2023-12-25 11:58:56	ga_ls9c_ard_3-2-1_116078_2023-12-25_final.stac-item
2024-01-03 10:09:47	ga_ls9c_ard_3-2-1_099068_2024-01-03_final.stac-item
2024-01-04 09:17:21	ga_ls9c_ard_3-2-1_090076_2024-01-03_final.stac-item
2024-02-04 10:09:50	ga_ls9c_ard_3-2-1_099068_2024-02-04_final.stac-item
2024-03-10 09:07:19	ga_ls9c_ard_3-2-1_088082_2024-03-09_final.stac-item
2024-03-14 11:58:44	ga_ls9c_ard_3-2-1_116078_2024-03-14_final.stac-item
2024-03-20 09:39:58	ga_ls9c_ard_3-2-1_094071_2024-03-20_final.stac-item
2024-03-22 09:35:11	ga_ls9c_ard_3-2-1_092090_2024-03-22_final.stac-item
2024-04-24 10:15:32	ga_ls9c_ard_3-2-1_099084_2024-04-24_final.stac-item
2024-04-27 09:06:46	ga_ls9c_ard_3-2-1_088082_2024-04-26_final.stac-item

Return to ga_ls9c_ard_3 whole collection overview

ga_ls9c_ard_3: Geoscience Australia Landsat 9 Operational Land Imager and Thermal Infra-Red Scanner Analysis Ready Data Collection 3

Baseline satellite data

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

All years